-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
      name:  <unnamed>
       log:  C:\Users\knm4642\Dropbox\Nha Meo Heo Beo\_JMP\WORKING FOLDER\Table II_Effect by industry and background.log
  log type:  text
 opened on:  18 Feb 2026, 23:44:45

. 
. //PREPARE DATA
. use "Baseline CEO firm year sample.dta", clear

. * construct additional variables
. gen pharmachem = inlist(sector, ///
>         "Chemicals", ///
>         "Pharmaceuticals and Biotechnology", ///
>         "Health")

. gen electroit = inlist(sector, ///
>         "Electronic & Electrical Equipment", ///
>         "Information Technology Hardware", ///
>         "Software & Computer Services")

. gen timesinceCEO = min(year - termstartyr, 9)

. gen postgradnonMBA = (education == 3 & MBA == 0) | education == 4

. gen hasRDexp = preCEO_resdir == 1 | preCEO_techdir == 1 

. * set globals
. global firm = "firmage firmage2"

. global ceo = "gender age age2 yrinco i.education"

. global sample = "year < 2012 & !nonUS"

. global cluster = "mainethcode"

. 
. 
. //PREPARE TABLE
. eststo clear

. eststo col1: /// pharma/chemical industries
>         reghdfe ash_f1allpat trust_sd ${firm} ${ceo} ///
>         if ${sample} & pharmachem, a(boardid year) cluster(${cluster}) keepsin
WARNING: Singleton observations not dropped; statistical significance is biased (link)
(MWFE estimator converged in 7 iterations)

HDFE Linear regression                            Number of obs   =      5,234
Absorbing 2 HDFE groups                           F(  10,     31) =      42.10
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.8643
                                                  Adj R-squared   =     0.8435
                                                  Within R-sq.    =     0.0057
Number of clusters (mainethcode) =         32     Root MSE        =     0.6327

                           (Std. err. adjusted for 32 clusters in mainethcode)
------------------------------------------------------------------------------
             |               Robust
ash_f1allpat | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
    trust_sd |   .0764197   .0347839     2.20   0.036     .0054775     .147362
     firmage |  -.0172272   .0083118    -2.07   0.047    -.0341792   -.0002752
    firmage2 |   .0003006   .0002321     1.29   0.205    -.0001728     .000774
      gender |   .0923159   .1447565     0.64   0.528    -.2029168    .3875487
         age |    -.00867   .0204684    -0.42   0.675    -.0504156    .0330755
        age2 |   .0000599   .0001785     0.34   0.740    -.0003042    .0004239
      yrinco |   .0091887   .0019874     4.62   0.000     .0051353    .0132421
             |
   education |
          2  |   .2236319   .1218529     1.84   0.076    -.0248887    .4721525
          3  |   .2246486   .1531917     1.47   0.153    -.0877878    .5370851
          4  |   .2316377   .1271538     1.82   0.078    -.0276941    .4909695
             |
       _cons |   1.027364   .5515465     1.86   0.072    -.0975228     2.15225
------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
     boardid |       675           0         675     |
        year |        12           1          11     |
-----------------------------------------------------+

.                 estadd local sample     "Pharma/chem"

added macro:
             e(sample) : "Pharma/chem"

.                 estadd local FE         "X"

added macro:
                 e(FE) : "X"

.                 estadd local controls   "X"

added macro:
           e(controls) : "X"

.                 distinct boardid if e(sample)

         |        Observations
         |      total   distinct
---------+----------------------
 boardid |       5234        675

.                 eststo col1, add(nofirms r(ndistinct))
(e(nofirms) = 675 added)

. eststo col2: /// pharma/chemical industries, by tenure as CEO
>         reghdfe ash_f1allpat c.trust_sd##c.timesinceCEO ${firm} ${ceo} ///
>         if ${sample} & pharmachem, a(boardid year) cluster(${cluster}) keepsin
WARNING: Singleton observations not dropped; statistical significance is biased (link)
(MWFE estimator converged in 7 iterations)

HDFE Linear regression                            Number of obs   =      5,234
Absorbing 2 HDFE groups                           F(  12,     31) =      52.63
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.8645
                                                  Adj R-squared   =     0.8437
                                                  Within R-sq.    =     0.0073
Number of clusters (mainethcode) =         32     Root MSE        =     0.6323

                                        (Std. err. adjusted for 32 clusters in mainethcode)
-------------------------------------------------------------------------------------------
                          |               Robust
             ash_f1allpat | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
--------------------------+----------------------------------------------------------------
                 trust_sd |    .012086   .0492203     0.25   0.808    -.0882996    .1124715
             timesinceCEO |  -.1199402   .0709922    -1.69   0.101    -.2647297    .0248493
                          |
c.trust_sd#c.timesinceCEO |   .0253066   .0141797     1.78   0.084    -.0036131    .0542262
                          |
                  firmage |  -.0177001   .0082774    -2.14   0.040    -.0345819   -.0008183
                 firmage2 |   .0002823   .0002283     1.24   0.226    -.0001834    .0007479
                   gender |   .0911292   .1411923     0.65   0.523    -.1968344    .3790929
                      age |  -.0133412   .0228766    -0.58   0.564    -.0599983     .033316
                     age2 |   .0000936   .0001941     0.48   0.633    -.0003022    .0004894
                   yrinco |   .0071584   .0027858     2.57   0.015     .0014768      .01284
                          |
                education |
                       2  |   .2414449   .1307601     1.85   0.074    -.0252421    .5081318
                       3  |   .2371092   .1596455     1.49   0.148      -.08849    .5627083
                       4  |   .2468957   .1365825     1.81   0.080    -.0316662    .5254577
                          |
                    _cons |   1.494101   .7024359     2.13   0.041     .0614731    2.926728
-------------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
     boardid |       675           0         675     |
        year |        12           1          11     |
-----------------------------------------------------+

.                 estadd local sample     "Pharma/chem"

added macro:
             e(sample) : "Pharma/chem"

.                 estadd local FE         "X"

added macro:
                 e(FE) : "X"

.                 estadd local controls   "X"

added macro:
           e(controls) : "X"

.                 distinct boardid if e(sample)

         |        Observations
         |      total   distinct
---------+----------------------
 boardid |       5234        675

.                 eststo col2, add(nofirms r(ndistinct))
(e(nofirms) = 675 added)

. eststo col3: /// ICT/electronic industries
>         reghdfe ash_f1allpat trust_sd ${firm} ${ceo} ///
>         if ${sample} & electroit, a(boardid year) cluster(${cluster}) keepsin
WARNING: Singleton observations not dropped; statistical significance is biased (link)
(MWFE estimator converged in 7 iterations)

HDFE Linear regression                            Number of obs   =      7,274
Absorbing 2 HDFE groups                           F(  10,     30) =       8.63
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.8989
                                                  Adj R-squared   =     0.8850
                                                  Within R-sq.    =     0.0029
Number of clusters (mainethcode) =         31     Root MSE        =     0.6591

                           (Std. err. adjusted for 31 clusters in mainethcode)
------------------------------------------------------------------------------
             |               Robust
ash_f1allpat | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
    trust_sd |   .0950543   .0456579     2.08   0.046     .0018084    .1883002
     firmage |  -.0129679   .0094036    -1.38   0.178    -.0321726    .0062368
    firmage2 |   .0001224   .0001609     0.76   0.453    -.0002063     .000451
      gender |   .0276968   .0708727     0.39   0.699    -.1170445    .1724382
         age |  -.0153179   .0243381    -0.63   0.534    -.0650231    .0343872
        age2 |   .0001123   .0002099     0.53   0.597    -.0003164    .0005411
      yrinco |   .0053209   .0019325     2.75   0.010     .0013743    .0092676
             |
   education |
          2  |   .0855322   .0885636     0.97   0.342    -.0953388    .2664033
          3  |   .1211833   .0730928     1.66   0.108     -.028092    .2704587
          4  |   .1243405    .064279     1.93   0.063    -.0069348    .2556157
             |
       _cons |   1.557039   .6456654     2.41   0.022     .2384145    2.875664
------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
     boardid |       862           0         862     |
        year |        12           1          11     |
-----------------------------------------------------+

.                 estadd local sample     "ICT/elec"

added macro:
             e(sample) : "ICT/elec"

.                 estadd local FE         "X"

added macro:
                 e(FE) : "X"

.                 estadd local controls   "X"

added macro:
           e(controls) : "X"

.                 distinct boardid if e(sample)

         |        Observations
         |      total   distinct
---------+----------------------
 boardid |       7274        862

.                 eststo col3, add(nofirms r(ndistinct))
(e(nofirms) = 862 added)

. eststo col4: /// ICT/electronic industries, by tenure as CEO
>         reghdfe ash_f1allpat c.trust_sd##c.timesinceCEO ${firm} ${ceo} ///
>         if ${sample} & electroit, a(boardid year) cluster(${cluster}) keepsin
WARNING: Singleton observations not dropped; statistical significance is biased (link)
(MWFE estimator converged in 7 iterations)

HDFE Linear regression                            Number of obs   =      7,274
Absorbing 2 HDFE groups                           F(  12,     30) =      11.07
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.8991
                                                  Adj R-squared   =     0.8851
                                                  Within R-sq.    =     0.0046
Number of clusters (mainethcode) =         31     Root MSE        =     0.6587

                                        (Std. err. adjusted for 31 clusters in mainethcode)
-------------------------------------------------------------------------------------------
                          |               Robust
             ash_f1allpat | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
--------------------------+----------------------------------------------------------------
                 trust_sd |   .1373812   .0534441     2.57   0.015     .0282337    .2465287
             timesinceCEO |   .0823826   .0633252     1.30   0.203    -.0469448    .2117099
                          |
c.trust_sd#c.timesinceCEO |  -.0137299   .0123675    -1.11   0.276    -.0389877    .0115278
                          |
                  firmage |  -.0136888   .0099564    -1.37   0.179    -.0340226     .006645
                 firmage2 |   .0000937   .0001745     0.54   0.595    -.0002626      .00045
                   gender |   .0294794   .0677229     0.44   0.666    -.1088291     .167788
                      age |  -.0206791   .0250935    -0.82   0.416    -.0719269    .0305687
                     age2 |    .000154   .0002161     0.71   0.482    -.0002874    .0005954
                   yrinco |   .0019022   .0018423     1.03   0.310    -.0018603    .0056646
                          |
                education |
                       2  |    .082106   .0874016     0.94   0.355    -.0963918    .2606039
                       3  |   .1184273   .0704646     1.68   0.103    -.0254807    .2623353
                       4  |   .1121091     .06269     1.79   0.084    -.0159209    .2401392
                          |
                    _cons |   1.514269   .6964487     2.17   0.038     .0919306    2.936607
-------------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
     boardid |       862           0         862     |
        year |        12           1          11     |
-----------------------------------------------------+

.                 estadd local sample     "ICT/elec"

added macro:
             e(sample) : "ICT/elec"

.                 estadd local FE         "X"

added macro:
                 e(FE) : "X"

.                 estadd local controls   "X"

added macro:
           e(controls) : "X"

.                 distinct boardid if e(sample)

         |        Observations
         |      total   distinct
---------+----------------------
 boardid |       7274        862

.                 eststo col4, add(nofirms r(ndistinct))
(e(nofirms) = 862 added)

. eststo col5: /// other industries
>         reghdfe ash_f1allpat trust_sd ${firm} ${ceo} ///
>         if ${sample} & !pharmachem & !electroit, a(boardid year) cluster(${cluster}) keepsin
WARNING: Singleton observations not dropped; statistical significance is biased (link)
(MWFE estimator converged in 7 iterations)

HDFE Linear regression                            Number of obs   =     16,876
Absorbing 2 HDFE groups                           F(  10,     34) =      11.05
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.9028
                                                  Adj R-squared   =     0.8892
                                                  Within R-sq.    =     0.0013
Number of clusters (mainethcode) =         35     Root MSE        =     0.4464

                           (Std. err. adjusted for 35 clusters in mainethcode)
------------------------------------------------------------------------------
             |               Robust
ash_f1allpat | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
    trust_sd |   .0364234   .0158662     2.30   0.028     .0041794    .0686674
     firmage |  -.0045417   .0011107    -4.09   0.000    -.0067989   -.0022845
    firmage2 |  -9.41e-06   .0000415    -0.23   0.822    -.0000937    .0000748
      gender |  -.0590593   .0435905    -1.35   0.184    -.1476458    .0295271
         age |   .0070142   .0053848     1.30   0.201     -.003929    .0179574
        age2 |  -.0000731   .0000457    -1.60   0.119     -.000166    .0000199
      yrinco |    .002241   .0007688     2.91   0.006     .0006785    .0038034
             |
   education |
          2  |   .0011714   .0313914     0.04   0.970    -.0626235    .0649663
          3  |   .0048761   .0346052     0.14   0.889    -.0654501    .0752023
          4  |   .0395987   .0361348     1.10   0.281     -.033836    .1130335
             |
       _cons |   .4096941   .1522902     2.69   0.011     .1002031    .7191851
------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
     boardid |      2061           0        2061     |
        year |        12           1          11     |
-----------------------------------------------------+

.                 estadd local sample     "Others"

added macro:
             e(sample) : "Others"

.                 estadd local FE         "X"

added macro:
                 e(FE) : "X"

.                 estadd local controls   "X"

added macro:
           e(controls) : "X"

.                 distinct boardid if e(sample)

         |        Observations
         |      total   distinct
---------+----------------------
 boardid |      16876       2061

.                 eststo col5, add(nofirms r(ndistinct))
(e(nofirms) = 2061 added)

. eststo col6: /// by CEO's education     
>         reghdfe ash_f1allpat c.trust_sd#i.postgradnonMBA postgradnonMBA ${firm} ${ceo} ///
>         if ${sample}, a(boardid year) cluster(${cluster}) keepsin
WARNING: Singleton observations not dropped; statistical significance is biased (link)
(MWFE estimator converged in 7 iterations)

HDFE Linear regression                            Number of obs   =     29,384
Absorbing 2 HDFE groups                           F(  12,     37) =      21.82
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.9014
                                                  Adj R-squared   =     0.8875
                                                  Within R-sq.    =     0.0025
Number of clusters (mainethcode) =         38     Root MSE        =     0.5426

                                        (Std. err. adjusted for 38 clusters in mainethcode)
-------------------------------------------------------------------------------------------
                          |               Robust
             ash_f1allpat | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
--------------------------+----------------------------------------------------------------
postgradnonMBA#c.trust_sd |
                       0  |   .0943916   .0219392     4.30   0.000     .0499386    .1388446
                       1  |  -.0093634   .0362978    -0.26   0.798    -.0829098     .064183
                          |
           postgradnonMBA |   .5153547    .253671     2.03   0.049     .0013683    1.029341
                  firmage |  -.0113241   .0019356    -5.85   0.000    -.0152461   -.0074021
                 firmage2 |   .0001142   .0000497     2.30   0.027     .0000136    .0002149
                   gender |  -.0130655   .0333601    -0.39   0.698    -.0806595    .0545285
                      age |  -.0016383   .0104703    -0.16   0.877    -.0228531    .0195765
                     age2 |  -2.87e-06   .0000861    -0.03   0.974    -.0001773    .0001716
                   yrinco |   .0040859   .0005541     7.37   0.000     .0029632    .0052085
                          |
                education |
                       2  |   .0431617   .0478517     0.90   0.373     -.053795    .1401184
                       3  |   .0628706   .0339303     1.85   0.072    -.0058787    .1316199
                       4  |   .0955267   .0488181     1.96   0.058    -.0033882    .1944415
                          |
                    _cons |   .6716684   .2944226     2.28   0.028     .0751115    1.268225
-------------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
     boardid |      3598           0        3598     |
        year |        12           1          11     |
-----------------------------------------------------+

.                 estadd local sample     "Full"

added macro:
             e(sample) : "Full"

.                 estadd local FE         "X"

added macro:
                 e(FE) : "X"

.                 estadd local controls   "X"

added macro:
           e(controls) : "X"

.                 distinct boardid if e(sample)

         |        Observations
         |      total   distinct
---------+----------------------
 boardid |      29384       3598

.                 eststo col6, add(nofirms r(ndistinct))
(e(nofirms) = 3598 added)

. eststo col7: /// by CEO's experience    
>         reghdfe ash_f1allpat c.trust_sd#i.hasRDexp hasRDexp ${firm} ${ceo} ///
>         if ${sample}, a(boardid year) cluster(${cluster}) keepsin
WARNING: Singleton observations not dropped; statistical significance is biased (link)
(MWFE estimator converged in 7 iterations)

HDFE Linear regression                            Number of obs   =     29,384
Absorbing 2 HDFE groups                           F(  12,     37) =      42.19
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.9013
                                                  Adj R-squared   =     0.8875
                                                  Within R-sq.    =     0.0022
Number of clusters (mainethcode) =         38     Root MSE        =     0.5427

                                  (Std. err. adjusted for 38 clusters in mainethcode)
-------------------------------------------------------------------------------------
                    |               Robust
       ash_f1allpat | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
--------------------+----------------------------------------------------------------
hasRDexp#c.trust_sd |
                 0  |   .0635729   .0151284     4.20   0.000     .0329198     .094226
                 1  |   .0005562   .1331137     0.00   0.997    -.2691578    .2702703
                    |
           hasRDexp |   .2979521   .6115311     0.49   0.629    -.9411276    1.537032
            firmage |  -.0110074    .001892    -5.82   0.000    -.0148409   -.0071739
           firmage2 |   .0001159   .0000491     2.36   0.024     .0000164    .0002154
             gender |  -.0124502   .0337422    -0.37   0.714    -.0808185     .055918
                age |  -.0013066   .0104545    -0.12   0.901    -.0224893    .0198762
               age2 |  -5.71e-06   .0000854    -0.07   0.947    -.0001787    .0001672
             yrinco |   .0041069   .0006488     6.33   0.000     .0027924    .0054214
                    |
          education |
                 2  |   .0434882   .0489096     0.89   0.380    -.0556121    .1425885
                 3  |   .0601535   .0340231     1.77   0.085     -.008784    .1290909
                 4  |   .0851727   .0426696     2.00   0.053    -.0012841    .1716296
                    |
              _cons |   .8121786   .3046933     2.67   0.011     .1948113    1.429546
-------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
     boardid |      3598           0        3598     |
        year |        12           1          11     |
-----------------------------------------------------+

.                 estadd local sample     "Full"

added macro:
             e(sample) : "Full"

.                 estadd local FE         "X"

added macro:
                 e(FE) : "X"

.                 estadd local controls   "X"

added macro:
           e(controls) : "X"

.                 distinct boardid if e(sample)

         |        Observations
         |      total   distinct
---------+----------------------
 boardid |      29384       3598

.                 eststo col7, add(nofirms r(ndistinct))
(e(nofirms) = 3598 added)

. 
. global coeflist1 = "trust_sd c.trust_sd#c.timesinceCEO"

. global coeflist2 = "0.postgradnonMBA#c.trust_sd 1.postgradnonMBA#c.trust_sd"

. global coeflist3 = "0.hasRDexp#c.trust_sd 1.hasRDexp#c.trust_sd"

. esttab /*using "Table II_Effect by industry and background.tex"*/, ///
>         cells(b(star fmt(3)) se(par fmt(3))) starlevels(* 0.1 ** 0.05 *** 0.01) ///
>         nomtitle collabels(none) label varwidth(32) modelwidth(12) ///
>         mgroups("arsinh(Future patent applications)", pattern(1 0 0 0 0 0 0) ///
>                 prefix(\multicolumn{@span}{c}{) suffix(}) span) ///
>         keep(${coeflist1} ${coeflist2} ${coeflist3}) order(${coeflist1} ${coeflist2} ${coeflist3}) ///
>         coeflab(trust_sd "CEO's trust" ///
>                         c.trust_sd#c.timesinceCEO "Trust $\times$ Tenure as CEO" ///
>                         0.postgradnonMBA#c.trust_sd "Trust $\times$ MBA/no grad deg" ///
>                         1.postgradnonMBA#c.trust_sd "Trust $\times$ Non-MBA grad deg" ///
>                         0.hasRDexp#c.trust_sd "Trust $\times$ No prior R\&D exp" ///
>                         1.hasRDexp#c.trust_sd "Trust $\times$ Prior R\&D exp") ///
>         stats(sample FE controls N nofirms, fmt(%9.0fc %9.0fc) ///
>                 lab("Sample" "Firm \& Year FEs" "Baseline controls" "Observations" "Firms"))

------------------------------------------------------------------------------------------------------------------------------------------------
                                 \multicolumn{7}{c}{arsinh(Future patent applications)}                                                         
                                          (1)             (2)             (3)             (4)             (5)             (6)             (7)   
------------------------------------------------------------------------------------------------------------------------------------------------
CEO's trust                             0.076**         0.012           0.095**         0.137**         0.036**                                 
                                      (0.035)         (0.049)         (0.046)         (0.053)         (0.016)                                   
Trust $\times$ Tenure as CEO                            0.025*                         -0.014                                                   
                                                      (0.014)                         (0.012)                                                   
Trust $\times$ MBA/no grad deg                                                                                          0.094***                
                                                                                                                      (0.022)                   
Trust $\times$ Non-MBA grad deg                                                                                        -0.009                   
                                                                                                                      (0.036)                   
Trust $\times$ No prior R\&D exp                                                                                                        0.064***
                                                                                                                                      (0.015)   
Trust $\times$ Prior R\&D exp                                                                                                           0.001   
                                                                                                                                      (0.133)   
------------------------------------------------------------------------------------------------------------------------------------------------
Sample                            Pharma/chem     Pharma/chem        ICT/elec        ICT/elec          Others            Full            Full   
Firm \& Year FEs                            X               X               X               X               X               X               X   
Baseline controls                           X               X               X               X               X               X               X   
Observations                            5,234           5,234           7,274           7,274          16,876          29,384          29,384   
Firms                                     675             675             862             862           2,061           3,598           3,598   
------------------------------------------------------------------------------------------------------------------------------------------------

. 
. cap log close
